D.R. Mani

ssGSEA3.0 improves statistical significance assessment in ssGSEA by using feature-level bootstrap resampling, enhancing detection power while maintaining calibration across weighting schemes.

In 174 sedentary adults, resistance exercise changed more muscle molecular features than endurance exercise across omes and time points; network analysis nominates MEF2A and NFIC as regulatory hubs.

The paper analyzes multi-omic, multi-tissue molecular responses to acute exercise in sedentary adults, identifying key pathways and exerkines involved in exercise effects.

The paper demonstrates that background proteome correction improves the accuracy of identifying dynamic protein-protein interactions by reducing false positives and negatives in AP-MS experiments.

This study identifies GAA accumulation in gliomas as a driver of neuronal activity and tumor growth, linking cancer metabolism to neuroscience through GABAA receptor activation.

This study uses in-situ glial cell-surface proteomics in Drosophila to identify DIP-β as a pro-longevity factor regulated by glial cells.

This study investigates Akap11 mutant mice to explore the neurobiological effects of AKAP11 loss, finding increased PKA activity and transcriptomic changes linked to schizophrenia and bipolar disorder.

This study identifies DNA hypomethylation, not DNA damage, as the primary mechanism of azacytidine and decitabine anti-cancer activity, linking it to chromatin regulators like USP48.

This paper presents an optimized workflow for high-throughput proteomic and phosphoproteomic analysis of FFPE tissues, achieving deep coverage and quantitative robustness comparable to TMT-based methods.

This paper evaluates kinase activity inference methods using phosphoproteomics data and benchmarking approaches, finding that curated kinase-substrate libraries significantly impact results.

This study identifies the intracellular signaling pathway of teneurins in synaptic partner matching using Drosophila models.

This study presents an automated single-cell proteomics workflow that identifies over 4,000 proteins per cell and detects key regulatory proteins in LPS-perturbed THP-1 cells.

This study identifies Acj6 as a transcription factor that controls dendrite targeting in Drosophila PNs by regulating combinatorial expression of cell-surface proteins.

The paper uses deep neural networks to predict gene perturbation from transcriptional profiles, achieving 74.9% accuracy but with limited generalizability due to data consistency issues.

PANOPLY is a cloud-based platform that automates and reproducibly analyzes proteogenomic data by integrating genomic, transcriptomic, proteomic, and post-translational modification data.

The paper identifies a blood protein biomarker signature to distinguish bacterial from viral/malaria pneumonia in children in a malaria-endemic setting, with high sensitivity and specificity.

The paper profiles cell-surface proteomes in Drosophila olfactory neurons across development, identifying new regulators of neural circuit assembly.